Lecture 2 | Convex Optimization II (Stanford)

Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues subgradients.

This course introduces topics such as subgradient, cutting-plane, and ellipsoid methods. Decentralized convex optimization via primal and dual decomposition. Alternating projections. Exploiting problem structure in implementation. Convex relaxations of hard problems, and global optimization via branch & bound. Robust optimization. Selected applications in areas such as control, circuit design, signal processing, and communications.

Complete Playlist for the Course:
http://www.youtube.com/view_play_list?p=3940DD956CDF0622

EE 364B Course Website:
http://www.stanford.edu/class/ee364b/courseinfo.html

Stanford University:
http://www.stanford.edu/

Stanford University Channel on YouTube:
http://www.youtube.com/stanford

Category:

Education

Tags:

• Math
• Technology
• Algebra
• calculus
• geometry
• electrical
• engineering
• convex
• optimization
• subgradient
• derivatives
• basic
• inequality
• function
• algorithms
• stepsize
• rules
• convergence
• results
• proofs
• optimal
• step
• size
• alternating
• projections

[cvoque]

@cooldood83 there are notes on the 364B website that contain proofs, etc...

[cooldood83]

In Convex Optimization II --- he seems to go superficial and skip a lot of proofs and just state things ... Convex optimization I was very detailed (atleast the book had all the details that you want) ... However, now i wonder which book he is teaching this from ...

[sreeramtube]

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